1. Oliver Bracht – CEO info@eoda.de Predictive Maintenance with R

2. Oliver Bracht – CEO info@eoda.de About eoda Predictive Maintenance Predictive Maintenance with R Best practice Agenda

3. Oliver Bracht – CEO info@eoda.de About eoda an interdisciplinary team of data scientists, engineers, economists and social scientists, founded 2010 in Kassel (Germany), specialized in analyzing structured and unstructured data, integrated portfolio for solving analytical problems, with a focus on „R“.

4. Oliver Bracht – CEO info@eoda.de Consulting Software Solution Training eoda portfolio

5. Oliver Bracht – CEO info@eoda.de Predictive Maintenance

6. Oliver Bracht – CEO info@eoda.de The past of maintenance Reactive or Breakdown Maintenance Preventive or Periodic Maintenance Condition-based Maintenance

7. Oliver Bracht – CEO info@eoda.de The past of maintenance Reactive or Breakdown Maintenance Preventive or Periodic Maintenance Condition-based Maintenance Unplanned production shutdowns Inefficient use of resources High monitoring costs

8. Oliver Bracht – CEO info@eoda.de The requirements on maintenance The future of maintenance Predictive Maintenance International competition Shorter product life cycles Faster technological leaps New business processes

9. Oliver Bracht – CEO info@eoda.de Predictive Maintenance Definition Predictive Maintenance as an extension of condition-based maintenance represents the informatization of production processes. With intelligent IT-based production systems Predictive Maintenance represents one important step on the path towards the development of a Smart Factory in industrial production.

10. Oliver Bracht – CEO info@eoda.de Predictive Maintenance Potential Analytic know-how Requirements of the market Domain Expertise

11. Oliver Bracht – CEO info@eoda.de Predictive Maintenance Time Data collection Data management Data analysis Planning of maintenance Maintenance Business Value Workflow

12. Oliver Bracht – CEO info@eoda.de Predictive Maintenance Data Collection and Management Environmental Data Sensor-based Machine Data Production indicators Big Data

13. Oliver Bracht – CEO info@eoda.de Predictive Maintenance Data analysis Source: David Smith Data Scientists Power User Administrative User Consumer

14. Oliver Bracht – CEO info@eoda.de Predictive Maintenance Data analysis Analysis steps Consumer User Data Scientists

15. Oliver Bracht – CEO info@eoda.de Predictive Maintenance Example – Gearbox Bearing damage in wind farm Reactive Maintenance Cost for a replacement of the bearing $ 250.000 Cran costs $ 150.000 Power generation / Revenue losses $ 26.000 $ 426.000 Source: http://www.wwindea.org/

16. Oliver Bracht – CEO info@eoda.de Predictive Maintenance Example – Gearbox Bearing damage in wind farm Predictive Maintenance Use of acceleration sensors, oil particle counters and weather forecast modules, plus reliable evaluation of the data  Early detection of the damage at the gearbox bearing Repair instead of exchange of the bearing $ 30.000 < $ 250.000 Lower cran costs $ 75.000 < $ 150.000 Power generation / Revenue losses $ 2.000 < $ 26.000 $ 107.000 < $ 426.000 Source: http://www.wwindea.org/

17. Oliver Bracht – CEO info@eoda.de Predictive Maintenance Potential factors 50 % Reduction of maintenance costs 50 % Reduction of machine damage 50 % Reduction of machine downtime 20 % Increase in machine lifetime 20 % Increase in productivity 25 % - 60% Profit growth Source: Barber, Steve & Goldbeck, P.: “Die Vorteile einer vorwärtsgerichteten Handlungsweise mit vorbeugenden und vorausschauenden Wartungstools und –strategien – konkrete Beispiele und Fallstudien.”

18. Oliver Bracht – CEO info@eoda.de Predictive Maintenance with R

19. Oliver Bracht – CEO info@eoda.de Predictive Maintenance with R Advantages Features The features that come with R (without additional investment) are incomparable R in the software stack

20. Oliver Bracht – CEO info@eoda.de Predictive Maintenance with R Advantages Features The features that come with R (without additional investment) are incomparable R in the analytic stack R can be integrated into all the layers of an analysis or reporting architecture C  Integration into an existing IT environment  Forecast on the machine Prototyping Implementation R directly on the machine

21. Oliver Bracht – CEO info@eoda.de Predictive Maintenance with R Advantages Features The features that come with R (without additional investment) are incomparable R in the analytic stack R can be integrated into all the layers of an analysis or reporting architecture Investment protection The involvement of the scientific community and large companies support the development and acceptance of R Quality R offers high reliability and uses the latest statistical methods Costs R is Open Source and there are no license costs

22. Oliver Bracht – CEO info@eoda.de Data Collection and Management Environmental Data Sensor-based Machine Data Production indicators Big Data Predictive Maintenance with R

23. Oliver Bracht – CEO info@eoda.de Data Collection and Management Environmental Data Sensor-based Machine Data Production indicators Different types of data at different times Predictive Maintenance with R TimeDensity 7:3015,3 8:3016,1 9:3015,7 10:3015,5 11:3016,0 12:3015,9 Big Data TimePressure 7:00235 8:00239 9:00240 10:00228 11:00231 12:00233

24. Oliver Bracht – CEO info@eoda.de Data Collection and Management Environmental Data Sensor-based Machine Data Production indicators Different types of data at different times Predictive Maintenance with R TimeDensity 7:3015,3 8:3016,1 9:3015,7 10:3015,5 11:3016,0 12:3015,9 TimePressure 7:00235 8:00239 9:00240 10:00228 11:00231 12:00233 Big Data Model based interpolation Density 15,4 16,0 15,7 15,4 15,8 16,1 Smart Data

25. Oliver Bracht – CEO info@eoda.de Data analysis Source: David Smith Data Scientists Power User User Consumer Predictive Maintenance with R

26. Oliver Bracht – CEO info@eoda.de Predictive Maintenance with R Best Practice

27. Oliver Bracht – CEO info@eoda.de Data Analysis Web based Front End Predictive Maintenance with R Best practice API Interactive Web App R- Scripts Java Script … Administration Authentication (LDAP) User-, Role- Management Session Management … Public data sources Internal data Machine data

28. Oliver Bracht – CEO info@eoda.de eoda GmbH Ludwig-Erhard-Straße 8 34131 Kassel Germany +49 (0) 561/202724-40 www.eoda.de http://blog.eoda.de https://service.eoda.de/ http://twitter.com/datennutzen https://www.facebook.com/datenwissennutzen info@eoda.de Thank you for your attention For more information Whitepaper: Predictive Maintenance with R www.eoda.de Results as a Service eoda Service Platform https://service.eoda.de/